System and Methods for Developing and Using a Microbiome-Based Action Component

2. The computer program according to claim 1, further comprising a line chart directed to “Microbiota for Age Z-Score”, the line chart with a y-axis representing a “Z-score” of the subject, the line chart including a plurality of points, wherein each point comprises a value for microbiota for an age of the subject with respect to a mean for a group of ‘healthy’ subjects at the same age and at the same day of life.

3. The computer program according to claim 1, further comprising a line chart with a second y-axis representing a gut community type, wherein the line chart indicates a stage of a gut community type (“GCT”).

4. The computer program according to claim 1, further comprising a line chart with a second y-axis representing a “weighted Z-score”, wherein the line chart indicates a weighted z-score describing a feed rate value compared to a mean for a group of feed rate values.

5. The computer program according to claim 1, wherein the factors identified in the second annulus for the non-modifiable risk factors category includes the factors: mode of birth, chronological or, in the case of a preterm infant gestational, age at birth, and gastrointestinal disease.

6. The computer program according to claim 1, wherein the factors identified in the second annulus for the perinatal and material risk factors category includes the factors: maternal diet, mother body mass index (BMI), perinatal steroid and antibiotic exposure, and maternal age.

7. The computer program according to claim 1, wherein the factors identified in the second annulus for the modifiable risk factors category includes the factors: nutrition, diet, antibiotic administration, and pre-/probiotics administration.

8. The computer program according to claim 1, wherein the factors identified in the second annulus for the microbiome-based measures of gut status category includes the factors: classification, stability, maturity.

10. The computer program according to claim 1, wherein the display includes a section providing “Birth and Growth Measures” comprising information for the subject including delivery mode, sex, weight, and a section providing “Predictive Measures” comprising one or more risk predictions of growth failure and non-typical development based on applying artificial intelligence/machine learning algorithms on clinical and/or microbiome data, at different time periods as well as actual growth and development.

11. The computer program according to claim 1, wherein a graph “Events, Fortification, Antibiotics” comprises icons such as circles, diamonds, squares, triangles representing one or more nutritional milestones, diagnoses, treatments, or occurrences comprising: return to birthweight (“RTBW”), Retinopathy of prematurity (“ROP”), Bronchopulmonary dysplasia (“BPD”).